Category Whitepapers and Guides
A gentle reminder as to why we need Automation, in a year where “Post-Truth” is Oxford Dictionaries’ Word of the Year.
Did you see this image making the rounds not so long ago? Did you spend as much time as I did trying to catch the dots off-guard, before they disappeared again? (sneaky buggers!)
What about this dress?
Do you see it as black and blue, or as white and gold? The internet was obsessed with it for a good few days, without reaching an agreement.
Objectivity tells us there’s 12 dots in the first image, located at the intersections, but our brain won’t allow us to see them all at once. Similarly, it lets us know that the dress was actually black and blue.
You don’t have to look much further than the climate change “debate” for evidence of inability for many people to see scientific arguments that go against their beliefs. Another good example is Brexit. 17 million people defied the ‘experts’, who prophesied a decade of doom, gloom and misery.
As somebody’s grandfather used to say, “The good thing about facts is that they are indifferent to your opinion.”
As 2016 draws to an end, we have seen the rise of the word “Post-Truth” and now we come into an age where “truth” itself, doesn’t even matter.
We have progressed from subjectivity to “truthiness” to an outright “post-truth” reality. A pick-your-own-reality adventure.
Confirmation bias is a cognitive bias that causes us to seek confirmation of our preconceptions, while we avoid information that might contradict them. It can also cause us to tend to overvalue information supporting our preconceptions, and undervalue information in conflict with them. 2016 has seen the rise of Extreme Confirmation Bias.
There have been many descriptions of the phenomenon of selective news consumption – information silos, confirmation bias – whereby the consumer assimilates information that conforms with pre-existing beliefs, and rejects contrary information. Google, Facebook, and others, use algorithms to identify the “content” we “prefer”, without our even knowing it, so we don’t even see other content.
This accelerates and amplifies the existing tendency.
The Rise of the Machine
2016 has also been the year where new technology has become the norm in our everyday lives.From TVs, computers, GPS, smartphones etc., we have seen the future come alive before our eyes. While technology has made our lives easier in many ways, it has also made us more reliant upon it.
As we enter 2017, I believe that the next big change we will see is the idea of the Internet of Things, specifically the industrial IoT. This means critical systems will come online and will need to be maintained by human processes.
A recent article by Forbes confirms that we’re going to see this digitisation in an unprecedented manner with “Half of Executives Worldwide Expecting Vast Digital Transformation in Next Two Years”.
These systems will need part or fully manual processes to maintain and deliver them e.g. Build and Release, Testing, Operations.
Software is designed, implemented and tested by people. Therefore, it is important to gain insight about people’s thought processes, and their problem solving skills, in order to improve software quality.
While solving problems during any phase of the Software Development Life Cycle (SDLC), software engineers employ some heuristics. These heuristics may result in “cognitive biases,” which are defined as patterned deviations of human thought from the laws of logic and mathematics.
You cannot fully avoid the confirmation bias. That’s actually a good thing, because if you could you wouldn’t be human.
We need Automation to make valid, objective inferences from data, free from this human bias.
ECS Digital are leaders in Automation and Digital Transformation. We’ve been helping enterprises deliver software and software-related services faster and at lower cost through the adoption of DevOps and Continuous Delivery practices, since 2003.
Read how we automated business processes for a leading Telco, enabling them to deliver 36 times faster than their main competitor, here.
Some credit must go to Matthew Mayo at KDnuggets: https://www.kdnuggets.com/2016/11/why-need-data-science.html, who partly inspired this piece.